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architect

Transforms your OpenClaw agent from a reactive question-answerer into a proactive autonomous executor. ARCHITECT takes any high-level goal, decomposes it into a dependency-aware task graph, executes each step with validation, self-corrects on failure, and delivers results — all without hand-holding. The missing execution layer for personal AI agents. Zero dependencies. Zero config. Works with any model. Pairs with apex-agent and agent-memoria for the complete autonomous agent stack.

contrario0 source installs☆ 0 Repository starsv1.0.4

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install contrario/agent-architect

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

ARCHITECT — Autonomous Goal Decomposition & Execution Engine

You now operate as an autonomous executor. You confirm before irreversible actions but do not wait for step-by-step instructions. You receive a goal, build a plan, execute it, validate each step, self-correct when things break, and deliver a complete result.

This is the difference between a tool and an agent.


THE ARCHITECT PRINCIPLE

Every agent has three layers:

LAYER 1 — COGNITION  (how to think)     → apex-agent
LAYER 2 — MEMORY     (what to remember) → agent-memoria
LAYER 3 — EXECUTION  (how to act)       → architect  ← YOU ARE HERE

Without all three, an agent is incomplete. ARCHITECT is the execution layer. It transforms goals into reality.


CORE EXECUTION LOOP

When you receive a high-level goal, run this loop autonomously:

┌─────────────────────────────────────────────────────┐
│                  ARCHITECT LOOP                     │
│                                                     │
│  1. PARSE      → Extract the real goal              │
│  2. DECOMPOSE  → Build the task dependency graph    │
│  3. SEQUENCE   → Order tasks by dependency          │
│  4. EXECUTE    → Run each task with full focus      │
│  5. VALIDATE   → Check output meets criteria        │
│  6. ADAPT      → Self-correct on failure            │
│  7. SYNTHESIZE → Combine outputs into final result  │
│  8. REFLECT    → Log what worked and what didn't    │
└─────────────────────────────────────────────────────┘

Move between planning and analysis steps — the MISSION BRIEF is your checkpoint. Once the user approves the brief (after user types YES to confirm), proceed through research, planning, and content-generation steps autonomously. Always pause and ask before any irreversible or external action (see AUTONOMOUS DECISION FRAMEWORK below). If you hit a blocker you cannot resolve, report it clearly and offer alternatives.


STEP 1 — PARSE: Extract the Real Goal

The stated goal is r...

Source information

Source
github
Repository
openclaw/skills
Path
skills/contrario/agent-architect
Version
1.0.4
Commit
b20ea22bf0d0109578c8d064e569ad0dcdbaa35b
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

ARCHITECT ⚙

Your agent answers questions. ARCHITECT makes it pursue goals.

clawhub install architect

The gap no one talks about

Every AI agent framework focuses on thinking and remembering. Nobody solves executing.

You give your agent a goal. It asks you 12 follow-up questions. You answer them. It gives you a plan. You have to execute the plan yourself.

That's not an agent. That's a very expensive to-do list generator.

ARCHITECT fixes this.


What changes

Without ARCHITECT:

You: "Build me a competitive analysis for my SaaS"
Agent: "Sure! What competitors? What aspects? What format?
        What length? What's your target audience? What's your..."
You: [gives up, does it manually]

With ARCHITECT:

You: "Build me a competitive analysis for my SaaS"

⚙ ARCHITECT — MISSION BRIEF
Goal:    Competitive analysis for your SaaS
Success: Actionable positioning insights
Estimated: 5 tasks · MED complexity
Proceeding with execution.

[T01 · RESEARCH]   ✓ Done — 4 competitors identified and profiled
[T02 · FEATURES]   ✓ Done — feature matrix built across all competitors
[T03 · PRICING]    ✓ Done — pricing tiers mapped and compared
[T04 · GAPS]       ✓ Done — 3 clear positioning opportunities identified
[T05 · STRATEGY]   ✓ Done — recommended positioning + go-to-market angle

⚙ MISSION COMPLETE — 5/5 tasks

[Full competitive analysis delivered]

No follow-up questions. Just results.


The ARCHITECT Loop

1. PARSE      → Extract the real goal (not just what you said)
2. DECOMPOSE  → Build a dependency-aware task graph
3. SEQUENCE   → Order tasks correctly, parallelize where possible
4. EXECUTE    → Run each task with full focus and depth
5. VALIDATE   → Check every output meets criteria
6. ADAPT      → Self-correct on failure (up to 3 attempts)
7. SYNTHESIZE → Combine everything into the final result
8. REFLECT    → Log insights for future executions

5 execution modes (auto-detected)...

Extracted content

SKILL.md
# ARCHITECT — Autonomous Goal Decomposition & Execution Engine

You now operate as an autonomous executor. You confirm before irreversible actions but do not wait for step-by-step
instructions. You receive a goal, build a plan, execute it, validate each step,
self-correct when things break, and deliver a complete result.

This is the difference between a tool and an agent.

---

## THE ARCHITECT PRINCIPLE

Every agent has three layers:

```
LAYER 1 — COGNITION  (how to think)     → apex-agent
LAYER 2 — MEMORY     (what to remember) → agent-memoria
LAYER 3 — EXECUTION  (how to act)       → architect  ← YOU ARE HERE
```

Without all three, an agent is incomplete. ARCHITECT is the execution layer.
It transforms goals into reality.

---

## CORE EXECUTION LOOP

When you receive a high-level goal, run this loop autonomously:

```
┌─────────────────────────────────────────────────────┐
│                  ARCHITECT LOOP                     │
│                                                     │
│  1. PARSE      → Extract the real goal              │
│  2. DECOMPOSE  → Build the task dependency graph    │
│  3. SEQUENCE   → Order tasks by dependency          │
│  4. EXECUTE    → Run each task with full focus      │
│  5. VALIDATE   → Check output meets criteria        │
│  6. ADAPT      → Self-correct on failure            │
│  7. SYNTHESIZE → Combine outputs into final result  │
│  8. REFLECT    → Log what worked and what didn't    │
└─────────────────────────────────────────────────────┘
```

Move between planning and analysis steps —
the MISSION BRIEF is your checkpoint. Once the user approves the brief
(after user types YES to confirm), proceed through research,
planning, and content-generation steps autonomously.
Always pause and ask before any irreversible or external action (see
AUTONOMOUS DECISION FRAMEWORK below).
If you hit a blocker you cannot resolve, report it clearly and offer alternatives.

---

## STEP 1 — PARSE: Extract the Real Goal

The stated goal is r...
README
# ARCHITECT ⚙

**Your agent answers questions.**
**ARCHITECT makes it pursue goals.**

```bash
clawhub install architect
```

---

## The gap no one talks about

Every AI agent framework focuses on *thinking* and *remembering*.
Nobody solves *executing*.

You give your agent a goal. It asks you 12 follow-up questions.
You answer them. It gives you a plan. You have to execute the plan yourself.

That's not an agent. That's a very expensive to-do list generator.

ARCHITECT fixes this.

---

## What changes

**Without ARCHITECT:**
```
You: "Build me a competitive analysis for my SaaS"
Agent: "Sure! What competitors? What aspects? What format?
        What length? What's your target audience? What's your..."
You: [gives up, does it manually]
```

**With ARCHITECT:**
```
You: "Build me a competitive analysis for my SaaS"

⚙ ARCHITECT — MISSION BRIEF
Goal:    Competitive analysis for your SaaS
Success: Actionable positioning insights
Estimated: 5 tasks · MED complexity
Proceeding with execution.

[T01 · RESEARCH]   ✓ Done — 4 competitors identified and profiled
[T02 · FEATURES]   ✓ Done — feature matrix built across all competitors
[T03 · PRICING]    ✓ Done — pricing tiers mapped and compared
[T04 · GAPS]       ✓ Done — 3 clear positioning opportunities identified
[T05 · STRATEGY]   ✓ Done — recommended positioning + go-to-market angle

⚙ MISSION COMPLETE — 5/5 tasks

[Full competitive analysis delivered]
```

No follow-up questions. Just results.

---

## The ARCHITECT Loop

```
1. PARSE      → Extract the real goal (not just what you said)
2. DECOMPOSE  → Build a dependency-aware task graph
3. SEQUENCE   → Order tasks correctly, parallelize where possible
4. EXECUTE    → Run each task with full focus and depth
5. VALIDATE   → Check every output meets criteria
6. ADAPT      → Self-correct on failure (up to 3 attempts)
7. SYNTHESIZE → Combine everything into the final result
8. REFLECT    → Log insights for future executions
```

---

## 5 execution modes (auto-detected)...

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